Methods for quantitative imaging of tissue shear modulus using acoustic radiation force induced shear waves have been proposed. Tissue shear modulus is thought to have significant diagnostic utility, and provides an image contrast mechanism distinct from that of conventional imaging modalities, e.g. B-mode ultrasound, X-ray CT. The ability to reliably quantify tissue modulus may reduce the need for tissue biopsy, and can allow longitudinal tracking of tissue response to therapy. (Edwin L. Carstensen, Kevin J. Parker, and Robert M. Lerner, “Elastography in the management of liver disease,” Ultrasound in Medicine and Biology, 34(10):1535-1546, 2008.) The use of acoustic radiation force to generate shear waves in tissue for the purpose of tissue characterization was first proposed by Sarvazyan. (Armen P. Sarvazyan, Oleg V. Rudenko, Scott D. Swanson, J. Brian Fowlkes, and Stanislav Y. Emelianov, “Shear wave elasticity imaging: a new ultrasonic technology of medical diagnostics,” Ultrasound in Medicine and Biology, 24(9):1419-1435, November 1998.)
Supersonic Shearwave Imaging (SSI), described by Bercoff, Tanter, and Fink, estimates tissue viscoelastic properties by tracking the progress of radiation force induced shear waves with an ultrafast scanner. (Jeremy Berco, Mickael Tanter, and Mathias Fink, “Supersonic shear imaging: A new technique for soft tissue elasticity mapping,” IEEE Transactions on Ultrasonics, Ferroelectronics and Frequency Control, 51(4):396-409, April 2004.) Multiple ultrasound tone bursts focused at a sequence of depths and transmitted in rapid succession are used to create a pair of large amplitude shear waves. The propagating shear waves are distorted by variations in shear modulus. Inversion algorithms applied to the tracked motion data are used to recover the shear modulus.
Palmeri et al. propose the Time-To-Peak (TTP) algorithm for shear modulus estimation. (M. L. Palmeri, M. H. Wang, J. J. Dahl, K. D. Frinkley, and K. R. Nightingale, “Quantifying hepatic shear modulus in vivo using acoustic radiation force,” Ultrasound in Medicine and Biology, 34(4):546-558, 2008). In this method a shear wave is generated by the acoustic radiation force of a short (10's of μs) focused ultrasound toneburst. Tissue motion lateral to the push beam is then tracked at multiple locations. The time to peak displacement at each location is taken as the “arrival time” of the shear wave. Knowledge of the arrival times and distance between the tracking locations allows the shear wave speed cs to be estimated. The shear modulus G is then determined through the relationship G=ρcs2, where ρ is the tissue density. A linear regression analysis of the measured arrival times is used to make the method more robust to noise.
The method of Shear Dispersion Ultrasound Vibrometery (SDUV) uses a time-varying radiation force to generate a harmonic shear wave. (S. Chen, M. Fatemi, and J. F. Greenleaf, “Shear property characterization of viscoelastic media using vibrations induced by ultrasound radiation force,” In Proceedings of the IEEE International Ultrasonics Symposium, volume 2, pages 1871-1875, 2002.) Ultrasonic tracking then measures tissue motion at known distances from the vibration source. The phase shift as a function of distance from the point of excitation is estimated from the motion data to determine the shear wavelength λ. Coupled with the known vibration frequency f, the shear modulus can estimated as G=ρ(λf)2.
In the TTP and SDUV methods, the propagation path length for the shear waves is assumed to be equal to the distance between the axes of the tracking beams used to measure the passage of the shear wave. With this assumption, estimation of shear wave speed would seem to be a simple matter of determining the time required by the shear wave to propagate past two observation points. However, a significant variance in the shear wave speed estimate is observed with this method, even within a homogeneous phantom. (M. L. Palmeri, M. H. Wang, J. J. Dahl, K. D. Frinkley, and K. R. Nightingale, “Quantifying hepatic shear modulus in vivo using acoustic radiation force,” Ultrasound in Medicine and Biology, 34(4):546-558, 2008; Stephen McAleavey, Erin Collins, Johanna Kelly, Etana Elegbe, and Manoj Menon, “Validation of smurf estimation of shear modulus in hydrogels,” Ultrasonic Imaging, 31:111-130, 2009.) The variation is consistent at a given observation point and not due to inadequate SNR. Therefore it cannot be reduced by temporal averaging, and spatial averaging of measurements is required to reduce the estimate variance. This spatial averaging, of course, reduces spatial resolution.
Our previous results suggest that the measurement noise is due to a speckle-induced variation in the effective distance between the track beams. (Stephen McAleavey, Erin Collins, Johanna Kelly, Etana Elegbe, and Manoj Menon, “Validation of smurf estimation of shear modulus in hydrogels,” Ultrasonic Imaging, 31:111-130, 2009.) Interference of the echo signal from discrete scattering sources within the tissue gives rise to areas of strong and weak reflection. The tracked echo along a given line will reflect the motion of the scatterers that most constructively interfere. These scatterers are not necessarily located on the beam axis, but are potentially displaced from it. The distance between the tracked points is not, then, simply the distance between the axes of ultrasound tracking beams, but rather a function of the two-way beam pattern and scatterer distribution at a given depth. A similar effect was noted by Ophir et al. in pulse-echo estimates of ultrasonic sound speed estimation. (J. Ophir, W. Johnson, Y. Yazdi, D. Shattuck, and D. Mehta, “Correlation artifacts in speed of sound estimation in scattering media,” Ultrasound in Medicine and Biology, 15(4):341-353, 1983.) Tracking beam spacings are on the order of 1-4 mm, while beamwidths can be on the order of 0.2-0.5 mm. Thus, this speckle-induced uncertainty in the path length can be a substantial fraction of the path length.
Typical ultrasound backscatter medical imaging systems (e.g., B-scan) use an aperture which is large compared to the ultrasound wavelength to generate a focused beam pattern on transmit and receive. Geometric focusing, either mechanical, electronic, or a combination of the two, is used to determine the phase of the aperture motion on transmit, and to adjust the echo phase on receive. In the linear theory, the frequency, size and apodization of the aperture determine the beam pattern. Deviations in assumed sound speed (cl=1540 m/s typically) of the media between the transducer and target can degrade the ideal beam pattern.
Often, as in medical imaging, the target to be imaged can support shear waves in addition to the longitudinal waves used for ultrasound imaging. Because of the near-incompressibility of tissue (Poisson's ratio nearly equal to 0.5), the shear wave speed is much lower than the longitudinal wave speed, and shear wave motion in the target can be tracked ultrasonically, as in many methods of elasticity imaging. The goal in elasticity imaging is to reconstruct the shear modulus of the object. The shearing of scatterers tends to decorrelate echo signals and ordinarily acts as a noise source (McAleavey et al., “Validation of SMURF estimation of shear modulus in hydrogels”).